How to Deal with Direct Traffic Source Data in Your Content Analytics
Marketing ROI

How to Deal with Direct Traffic Source Data in Your Content Analytics

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Your ability to know your audience personally will set you apart from your competition. When you lose your advantage in the marketplace due to a lack of customer insight, a misunderstanding of incoming data, or simply disorganized measurement systems, you put the future of your business at risk. So when you start seeing an increase in untraceable referral traffic from unknown sources, it can be extremely frustrating for your entire analytics team; it can essentially make an important source of data obsolete.

Let’s say 25 percent of your digital publication’s traffic shows up as “direct.” That’s 25 percent of your audience that you don’t know very well (are they coming from an email? Has a link be sent around a private community? Are your URL parameters being stripped somewhere due to a breakdown in your distribution strategy?). All of these represent crucial gaps in how you measure your content strategy’s success and mark missed opportunities for your sales and marketing teams, respectively.

Picture a theater, where house lights illuminate only three-quarters of the audience. As the performer, you can’t see those sitting in the final rows of seats, and therefore your acting becomes less directed toward them and those attendees begin to feel a little more left out.

Luckily, there are ways around this issue—it’s crucial to accurately pinpoint your traffic’s source and medium. Medium is defined by Google as “the general category of the source, for example, organic search (organic), cost-per-click paid search (CPC), Web referral (referral).”

Referral traffic on a websiteHow Referral Traffic Works

Referral traffic is how Google tracks visits that came from a source outside the search engine. For example, a user might arrive on a landing page via a bookmark or simply by typing the URL into the search bar. According to Search Engine Land, more than half of direct traffic comes from organic search, but due to browser issues, Google may not be able to detect this.

Even if this is the most likely scenario, there are dozens of other reasons why Google may credit some incoming traffic to “(direct)/(none)” referral traffic. A lot of bot traffic, search engine crawlers, and spam gets lumped into this category. If you’re seeing a continuous rise in untraceable referral traffic and your keyword rankings aren’t approving across search engines, you might have a growing issue with bot traffic. If it begins to throw your data off, impacting bounce rate, exit rate, and time on page, you might want to consider blocking any repeat offending IP addresses. This will help bring clarity to your data sources.

Common Referral Source Issues—and How to Fix Them

Some of the most common reasons referral sources might not be detected are from clicking links on external sources such as email, clicking a link from a mobile application, or jumping from a secure site to a non-secure site, as a result of using URL shorteners (or simply because of browser technicalities). If the required tagging and parameters are set up correctly and at the start of a campaign, many subsequent complications can be avoided. For example, a tag that distinguishes mobile traffic from desktop traffic.

To learn how to set up custom campaign parameters for your URL’s, check out Google’s guide.

Although you may not be able to completely recover the sources of all your direct traffic, there are methods to better refine this metric and maximize its value for your content measurement KPIs. Adding parameters or tracking tags to all URLs used in a campaign is the first step in decreasing your direct traffic volume. As an example, miscategorization of mobile traffic can be mitigated by including parameters, like tags, that make sure all sessions from this referrer source shows up as “mobile” in GA reporting. A tag is a way of isolating a specific metric in order to isolate it for measurement purposes. Distinguishing traffic sources can provide understanding of user motivation and more granular content analytics, such as views, social engagement, referrer source, conversion rates or open rates.

URL shorteners alter the long-winded URL into a more streamlined version, providing convenience to the user in terms of sharing content. GA Twitter and Bitly are known for utilizing URL shorteners, in turn making it more challenging for GA to accurately track this referral traffic. The referral source gets lost in the URL redirect process and is then reported as direct. As a result, this will skew content analytics. In order to decrease the percentage of direct traffic resulting from this, any URL originating from shorteners should be tagged as such. Furthermore, these visits will not be correctly attributed to the social section of a GA report without the proper parameters being implemented.

Although it takes some digging, there is usually a way to get an answer to any inaccuracy in your data. Not only is accuracy vital in itself, it can end up providing tangible value to the business.

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